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Regression analysis of multivariate panel count data with an informative observation process

Author

Listed:
  • Zhang, Haixiang
  • Zhao, Hui
  • Sun, Jianguo
  • Wang, Dehui
  • Kim, KyungMann

Abstract

Multivariate panel count data arise in event history studies on recurrent events if there exist several related events and study subjects can be examined or observed only at discrete time points instead of over continuous periods. In these situations, a complicated issue that may arise is that the observation time points or process may be related to the underlying recurrent event process of interest. That is, we have informative observation processes. It is obvious that to perform a valid analysis, both the relationship among different types of recurrent events and the informative observation process need to be taken into account. To address these, we propose a robust joint modeling approach. For the estimation of regression parameters, an estimating equation-based inference procedure is developed and the asymptotic properties of the resulting estimates are established. Numerical studies indicate that the proposed approach works well for practical situations and the methodology is applied to a skin cancer study that motivates this study.

Suggested Citation

  • Zhang, Haixiang & Zhao, Hui & Sun, Jianguo & Wang, Dehui & Kim, KyungMann, 2013. "Regression analysis of multivariate panel count data with an informative observation process," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 71-80.
  • Handle: RePEc:eee:jmvana:v:119:y:2013:i:c:p:71-80
    DOI: 10.1016/j.jmva.2013.04.012
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    References listed on IDEAS

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    1. Chiung-Yu Huang & Mei-Cheng Wang & Ying Zhang, 2006. "Analysing panel count data with informative observation times," Biometrika, Biometrika Trust, vol. 93(4), pages 763-775, December.
    2. Jianguo Sun, 2003. "A nonparametric test for panel count data," Biometrika, Biometrika Trust, vol. 90(1), pages 199-208, March.
    3. Ying Zhang, 2002. "A semiparametric pseudolikelihood estimation method for panel count data," Biometrika, Biometrika Trust, vol. 89(1), pages 39-48, March.
    4. Lin D Y & Ying Z, 2001. "Semiparametric and Nonparametric Regression Analysis of Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 103-126, March.
    5. X. Joan Hu & Jianguo Sun & Lee‐Jen Wei, 2003. "Regression Parameter Estimation from Panel Counts," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 25-43, March.
    6. N. Balakrishnan & Xingqiu Zhao, 2011. "A class of multi-sample nonparametric tests for panel count data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(1), pages 135-156, February.
    7. Lin D Y & Wei L J & Ying Z, 2001. "Semiparametric Transformation Models for Point Processes," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 620-628, June.
    8. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
    9. Zhao, Xingqiu & Tong, Xingwei & Sun, Jianguo, 2013. "Robust estimation for panel count data with informative observation times," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 33-40.
    10. J. Sun & L. J. Wei, 2000. "Regression analysis of panel count data with covariate‐dependent observation and censoring times," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 293-302.
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    Citations

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    Cited by:

    1. Li, Yang & He, Xin & Wang, Haiying & Zhang, Bin & Sun, Jianguo, 2015. "Semiparametric regression of multivariate panel count data with informative observation times," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 209-219.
    2. Yang Li & Xin He & Haiying Wang & Jianguo Sun, 2016. "Regression analysis of longitudinal data with correlated censoring and observation times," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(3), pages 343-362, July.
    3. Jie Zhou & Haixiang Zhang & Liuquan Sun & Jianguo Sun, 2017. "Joint analysis of panel count data with an informative observation process and a dependent terminal event," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(4), pages 560-584, October.
    4. Deng, Shirong & Liu, Kin-yat & Zhao, Xingqiu, 2017. "Semiparametric regression analysis of multivariate longitudinal data with informative observation times," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 120-130.
    5. Yao, Bin & Wang, Lianming & He, Xin, 2016. "Semiparametric regression analysis of panel count data allowing for within-subject correlation," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 47-59.
    6. Jie Zhou & Haixiang Zhang & Liuquan Sun & Jianguo Sun, 0. "Joint analysis of panel count data with an informative observation process and a dependent terminal event," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 0, pages 1-25.

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